1. Field of the Invention
The present disclosure relates to image processing, and more particularly to a system and method for automatic image registration using prior information from pre-aligned image pairs.
2. Description of Related Art
A typical image registration algorithm has three components; a registration measure that quantifies a similarity between two images; a transformation space that determines allowed spatial transformations; and an optimization scheme to search the allowed spatial transformations for a transformation that maximizes (or minimizes) the registration measure.
The problem of using prior information to improve multi-modal registration performance has been suggested by Leventon et al. They propose estimating the underlying joint prior intensity distribution of registered image pairs using training data and employing a maximum likelihood approach to define the registration measure for new image pairs. Subsequently, Chung et al., proposed an alternative approach in which the quality of registration is determined by a Kullback-Leibler divergence between the estimated joint intensity distribution of pre-aligned data and the joint intensity distribution of the new images. Registration is then accomplished by minimizing this K-L divergence. Both Leventon and Chung have indicated experimentally that using prior information improves the robustness of registration methods.